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Detection of images degraded by rain using image quality assessment

Identifikátory výsledku

  • Kód výsledku v IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62690094%3A18450%2F22%3A50019131" target="_blank" >RIV/62690094:18450/22:50019131 - isvavai.cz</a>

  • Výsledek na webu

    <a href="https://link.springer.com/article/10.1007/s11042-022-13041-5" target="_blank" >https://link.springer.com/article/10.1007/s11042-022-13041-5</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1007/s11042-022-13041-5" target="_blank" >10.1007/s11042-022-13041-5</a>

Alternativní jazyky

  • Jazyk výsledku

    angličtina

  • Název v původním jazyce

    Detection of images degraded by rain using image quality assessment

  • Popis výsledku v původním jazyce

    Various weather conditions degrade images, and hence the quality of the images is compromised to a large extent. Atmospheric conditions like Rain, Fog, Haze, Mist, etc., degrade scenes, and the scene&apos;s acquisition results in noisy images. The noisy images have less visibility than regular images. Therefore, the images degraded by the weather conditions need some special attention before processing them. Otherwise, the processing of noisy images using the same process applied for noise-free images cannot find the desired results. Hence, the identification of images degraded by weather conditions is essential before further processing. Rain is one of the most complex atmospheric conditions that degraded images. In the case of rain, water droplets present in the air are visible, wherein,in other atmospheric conditions, water droplets cannot be seen. In rainy images, the large size of water droplets in the air causes more complex degradation. This research paper has proposed a technique for detecting images degraded by rain using an image quality assessment approach. We have used no-reference image quality assessment techniques for this work. We have proposed an image quality metric specially designed for the images degraded by rain. We have used the proposed metric along with other state-of-the-art metrics for identifying rainy images. Our proposed technique has been evaluated using a public dataset containing about 1500 images. We found promising results by applying our technique to that dataset to detect images degraded by rain. This technique can help security and surveillance applications, where the automatic selection of degraded frames is crucial.

  • Název v anglickém jazyce

    Detection of images degraded by rain using image quality assessment

  • Popis výsledku anglicky

    Various weather conditions degrade images, and hence the quality of the images is compromised to a large extent. Atmospheric conditions like Rain, Fog, Haze, Mist, etc., degrade scenes, and the scene&apos;s acquisition results in noisy images. The noisy images have less visibility than regular images. Therefore, the images degraded by the weather conditions need some special attention before processing them. Otherwise, the processing of noisy images using the same process applied for noise-free images cannot find the desired results. Hence, the identification of images degraded by weather conditions is essential before further processing. Rain is one of the most complex atmospheric conditions that degraded images. In the case of rain, water droplets present in the air are visible, wherein,in other atmospheric conditions, water droplets cannot be seen. In rainy images, the large size of water droplets in the air causes more complex degradation. This research paper has proposed a technique for detecting images degraded by rain using an image quality assessment approach. We have used no-reference image quality assessment techniques for this work. We have proposed an image quality metric specially designed for the images degraded by rain. We have used the proposed metric along with other state-of-the-art metrics for identifying rainy images. Our proposed technique has been evaluated using a public dataset containing about 1500 images. We found promising results by applying our technique to that dataset to detect images degraded by rain. This technique can help security and surveillance applications, where the automatic selection of degraded frames is crucial.

Klasifikace

  • Druh

    J<sub>imp</sub> - Článek v periodiku v databázi Web of Science

  • CEP obor

  • OECD FORD obor

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Návaznosti výsledku

  • Projekt

  • Návaznosti

    I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Ostatní

  • Rok uplatnění

    2022

  • Kód důvěrnosti údajů

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Údaje specifické pro druh výsledku

  • Název periodika

    Multimedia Tools and Applications

  • ISSN

    1380-7501

  • e-ISSN

    1573-7721

  • Svazek periodika

    81

  • Číslo periodika v rámci svazku

    24

  • Stát vydavatele periodika

    NL - Nizozemsko

  • Počet stran výsledku

    17

  • Strana od-do

    35445-35461

  • Kód UT WoS článku

    000784679300018

  • EID výsledku v databázi Scopus

    2-s2.0-85128549009